Also known as Radio Pattern Matching or Radio Signature positioning, Fingerprinting technologies represent a family of Path Loss based technologies that rely on matching the Radio Frequency (RF) environment, as experienced by the User Equipment (UE), to the known or estimated or otherwise mapped characteristics of the larger RF System in which the UE is operating. Information from the UE, including measurements of neighbor cell signal strengths, time delay and other network parameters form the basis of the RF environment to be compared to the established system RF Database. The intent of this approach is to mitigate the negative impacts of anomalies within the RF environment that challenge the accuracy of trilateration technologies (e.g. multipath and reflection).
The RF fingerprinting positioning method is based on measurements made by the UE and Base Station. The essential measurement set required for this method is currently defined in [3GPP TS 25.215—expand reference] and necessary for the basic mobility functionality and hence this method will work with existing mobiles without any modification.
Fingerprinting positioning algorithms operate by creating a radio fingerprint for each point of a fine coordinate grid that covers the Radio Access Network (RAN). Each such measurement may be associated with an identity (ID) of a Radio Base Station (RBS). A database with fingerprints is associated with true positions on the ground—radio related measurements of mobile device/user equipment may then be matched with this database to obtain their position. The fingerprint may e.g. consist of:                The cell Ids that are detected by the terminal, in each grid point.        Quantized path loss or signal strength measurements, with respect to multiple RBSs, performed by the terminal, in each grid point.        Quantized Round Trip Time (RTT), in Wideband Code Division Multiple Access (WCDMA), or Timing Advance (TA), in Global System for Mobile communications (GSM) and Long Term Evolution (LTE), or UE Rx-Tx time difference (in LTE) in each grid point.        Quantized noise rise, representing the load of a CDMA system, in each grid point.        Quantized signal quality e.g. RxQual in GSM, Ec/N0 in WCDMA and RSRQ in LTE.        Radio connection information like the radio access bearer (RAB).        Quantized time.        
The source of the fingerprint can be:                A driving test is performed that operator uses tool such as TEMS (http://www.ascom.com/en/index/group/divisions/network-testing-home.htm?_metal-site=US&_metal-lang=en) to collect data along the road, and use the collected data to populate the fingerprint database. This is usually known as offline collection.        During normal positioning session which high accuracy positioning methods, e.g. Assisted GPS (A-GPS), Observed Time Difference Of Arrival (positioning method) (OTDOA) etc., are available, the positioning result from the high accuracy methods together with the radio data can be used to populate the fingerprint database. This is usually known as online collection.        Based on the popular propagation model such as Cost 231-Hata, SPM (Standard Propagation Model) etc. which is frequently used in cell planning and related researches, the signal strength/quality can be simulated in the target area. Those “Virtual” data can be used to populate the fingerprint database.        
Whenever a position request arrives, a radio fingerprint is first measured, after which the corresponding grid points with similar characteristic are looked up and a location estimate is calculated and reported.
AECID (Adaptive Enhanced Cell ID) developed by the applicant is one kind of fingerprinting positioning technology that refines the basic cell identity positioning method in a variety of ways.
AECID has been described in US-2004/0203856 as well as in the following publications:                T. Wigren, “Adaptive enhanced cell ID fingerprinting localization by clustering of precise position measurements”, IEEE Trans. Veh. Tech., vol. 56, pp. 3199-3209, 2007        L. Shi and T. Wigren, “AECID fingerprinting positioning performance”, in Proc. Globecomm 2009, Honolulu, U.S.A, pp. 2767-2772, Nov. 30-Dec. 4, 2009.        
The AECID positioning method is based on the idea that high precision positioning measurements, e.g. A-GPS measurements, can be seen as points that belong to regions where certain cellular radio propagation condition persist.
In a first step A-GPS positioning is performed at the same time of UE network signal measurement. The AECID positioning method introduces a tagging of high precision measurements according to certain criteria, e.g. including                The cell Ids that are detected by the terminal, in each grid point.        Quantized path loss or signal strength measurements, w.r.t. multiple RBSs, performed by the terminal, in each grid point.        Quantized Round Trip Time (RTT, in WCDMA) or Timing Advance (TA, in GSM and LTE), or UE Rx-Tx time difference(in LTE) in each grid point.        Quantized noise rise, representing the load of a CDMA system, in each grid point.        Quantized signal quality e.g. RxQual in GSM, Ec/N0 in WCDMA and RSRQ in LTE.        Radio connection information like the radio access bearer (RAB).        Quantized time.        
The tag consist of a vector of indices, each index taking an enumerable number of discrete values. Continuous variables used for tagging, like path loss, hence need to be quantized.
In a second step collect all high precision positioning measurements that have the same tag in separate high precision measurement clusters, and perform further processing of said cluster in order to refine it. Geographical region can be smaller than the extension of a cell of the cellular system.
In a third step a polygon that represents the geographical extension of a cluster is computed, for each stored high precision position measurement cluster. The two most pronounced properties of the algorithm include:                The area of the polygon is minimized (accuracy hence maximized).        The probability that the terminal is within the polygon (the confidence) is precisely known (it is set as a constraint in the algorithm).        
In a fourth step, for an incoming positioning request, the UE's network measurement is firstly obtained. By looking up cell Ids or tags, the polygon corresponding to the determined tag is then looked up in the tagged database of polygons, followed by reporting, e.g. over RANAP using the polygon format.
A Serving Mobile Location Center (SMLC)—SMLC interface is defined for GSM EDGE (Enhanced Data Rates for GSM Evolution) Radio Access Network (GERAN) by The 3rd Generation Partnership Project 3GPP in TS 43.059 V10.0.0 (2011 March). The 3rd Generation Partnership Project 3GPP has in TS 25.453 V10.3.0 (2011 June) standardized Universal Terrestrial Radio Access Network (UTRAN) Iupc interface Positioning Calculation Application Part (PCAP) signaling. In the UTRAN context, an SMLC can be located inside a Radio Network Controller (RNC) or as Standalone SMLC (SAS). Despite that an SMLC-SMLC interface is defined for GERAN in TS 43.059, the UTRAN specification TS 25.453 does not specify such interface in architecture or for positioning signaling flow
There are needs for location services that require both location accuracy and user transparency (Government Surveillance and Lawful Intercept). These services cannot be addressed with location technologies which require UE support or modification, for example Assisted GPS (A-GPS) or Observed Time Difference Of Arrival (OTDOA). Additionally, Emergency Service applications require a level of location accuracy which cannot be met with Cell-ID and RTT. The potential benefits of RF fingerprinting and the relative ease with which this location method can be adopted in the UTRAN would indicate that it is appropriate that the technology be included in the UTRAN in support of the services noted above, as well as for cooperative deployment with satellite-based systems, A-GPS, Assisted Global Navigation Satellite System (GNSS) (A-GNSS) etc., in support of “Hybrid” location technology for Location Based Services (LBS).
Because of the lacking standardization for UTRAN, there is a need, in particular in multi-vendor situations, for a solution allowing access to a mobile location center, for example having capability for specific positioning methods such as fingerprinting or AECID, with minor impact on existing standards.